AdapTrack: An adaptive FairMOT tracking method applicable to marine ship targets

Abstract

Ship tracking at sea is faced with the disadvantages of complex sea conditions and the large influence of ship occlusion on the tracker. Therefore, we propose a method called AdapTrack based on On the Fairness of Detection and Re-Identification in Multiple Object Tracking (FairMOT) which is suitable for marine targets. The search strategy of trivial augmentation is used to randomly select suitable data augmentation methods and strengths. Then, based on the FairMOT tracking framework, we change the sampling selection method of positive and negative samples from a two-dimensional Gaussian distribution with the same variances to a two-dimensional Gaussian distribution with different variances. It is limited by the bounding box (bbox) of ground truth. This method can improve the detection algorithm’s fitness to the ship target. At the same time, we use Multi-Object Tracking by Associating Every Detection Box (ByteTrack)’s double-threshold strategy to divide detection bboxes, which improves the matching and inference speed. In the first stage of data association, the high-scoring bbox calculates the cost matrix of data association through the Re-identification (Re-ID) model. In the second stage, the Intersection over Union(IOU) cost matrix is calculated after merging low-scoring detection bboxes and unmatched detection bboxes of the first stage. The method achieves Multiple Object Tracking Accuracy (MOTA) of 36.1, Identification F-Score (IDF1) of 47.3, and Frames Per Second (FPS) of 28.79 on the Singapore-Marine-dataset. Experiments show that this method can better alleviate Identification Switch (ID-switch) and ensure the real-time tracking of complex and changeable ship target tracking at sea.